A Self-optimised Tableting DataFactory: Accelerating Process and Formulation Development

DRA lecture held by Professor Daniel Markl, University of Strathclyde, UK

BIOSKETCH – Professor Daniel Markl
Daniel Markl is a Professor in Pharmaceutical Product Engineering at the University of Strathclyde and Associate Director at the Centre for Continuous Manufacturing and Advanced Crystallisation (CMAC). His research aims to develop cyber-physical systems and associated, innovative methods for drug product development and manufacturing that accelerate the pace at which new medicines are developed and delivered across important therapeutic areas. This includes the coupling of advanced measurement techniques with digital process and product design tools to resolve the relationship between material attributes, manufacturing conditions and the performance and stability of solid oral dosage forms. 

ABSTRACT
Traditional methods of developing drug products for a new active pharmaceutical ingredient are time-consuming, costly and often inflexible. The selection of the right excipients in tablets and process conditions are crucially important as they can impact manufacturability, performance and stability of the drug product. Formulation optimisation studies are conducted to identify a robust formulation that can meet manufacturability criteria (e.g. flowability, tensile strength) while fulfilling the desired performance targets, e.g. release of > 80% of the drug in less than 30 min. This is a multidimensional optimisation problem with a high degree of interdependence between raw material attributes, process parameters, and drug product properties. These complex relationships cannot be fully captured by first principle models and it is not feasible, in a reasonable time, to experimentally optimise these multidimensional formulation (type of excipient, concentration, drug loading) and process parameter (e.g. compression forces, dwell time) spaces following traditional experimental planning and methods. This talk will present a self-driving, high-throughput, data-intensive micro-scale tablet development system – a tableting DataFactory - that can automatically prepare and measure powder, and produce and test single tablets. By employing robots, the system combines an automated dosing unit, a dedicated powder transportation unit, near-infrared spectroscopy for evaluating powder blend homogeneity, a compaction simulator, and an automated testing system for measuring tablet properties. The data is automatically structured and fed into a database for the development of a hybrid system of models, including mechanistic and data-driven (AI) approaches, to predict critical powder blend (e.g. flowability) and tablet attributes (tensile strength, porosity) from raw material properties. This talk will further discuss the combination of hybrid modelling approaches with model-based optimisation and the micro-scale tablet development system. This approach substantially reduces hands-on-lab time (> 80%), material, and waste, offering significant potential for accelerated and sustainable drug product development.

The lecture is organized on behalf of the graduate programme in pharmaceutical sciences, Drug Research Academy, by Professor Jukka Rantanen, Department of Pharmacy, Faculty of Health and Medical Sciences, University of Copenhagen.

The DRA lecture is free of charge and open for attendance by all interested parties. It is not necessary to pre-register.